Skill UI

This tool guides users through the entire process of transforming a raw, conceptual invention idea into a highly structured, formal invention disclosure suitable for patent filing. It follows established patent writing frameworks, including Problem-Solution-Advantage decomposition, core inventive concept isolation, and detailed claim drafting (method, system, product). Ideal for engineers, researchers, and inventors needing to formalize their intellectual property documentation.

This comprehensive skill guides users through the entire Fluid storage extension lifecycle within KubeSphere. It allows for installing, upgrading, and uninstalling the Fluid extension, and managing various data resources. Users can generate YAML manifests for Datasets and specialized runtimes (Alluxio, JuiceFS, Thin), perform data loading/cache warming, scale operations, and troubleshoot issues using both kubectl and KubeSphere APIs.

This skill generates standardized, production-ready `mise.toml` configurations. It helps developers standardize runtime versions across mixed-language projects (e.g., Node.js, Python, Go, etc.) and CI/CD pipelines, eliminating the need for multiple legacy version managers like asdf or nvm. Ideal for ensuring reproducible, consistent development environments.

This utility publishes various Aegis-related events (such as person detection, alerts, and clip completion) to an MQTT broker. It is designed for seamless integration with smart home and automation platforms like Home Assistant or Node-RED, enabling real-time, event-driven monitoring and system linkage.

This guide provides a comprehensive, advanced methodology for red team operations. It covers critical topics such as Operational Security (OPSEC), designing robust C2 infrastructure using redirectors, employing living-off-the-land techniques, mastering lateral movement, establishing persistence, and planning data exfiltration while evading modern defensive systems. Use this to plan complex red team engagements or deeply understand Advanced Persistent Threat (APT) TTPs.

A comprehensive guide for migrating cloud workloads from AWS or Azure to Oracle Cloud Infrastructure (OCI). It provides detailed concept mapping for core services like IAM, networking (VPC/VCN), compute (AMI/Custom Image), and data storage. The skill covers end-to-end migration procedures, including using OCI CLI and Python SDK for controlled deployment and resource translation.

This skill provides a deep dive into optimizing Oracle Cloud Infrastructure (OCI) resources. It guides users through selecting appropriate compute shapes (e.g., E5.Flex, A1.Flex) and understanding the performance tiers for block volumes (Balanced, Ultra High Performance). Users can programmatically query available shapes, create performance-tuned volumes, and monitor real-time IOPS and network bandwidth using the OCI SDK, ensuring optimal infrastructure decisions for any workload.

A comprehensive checklist designed to validate that an Oracle Cloud Infrastructure (OCI) environment meets rigorous production-grade standards. This tool automates checks for critical security controls, including compartment isolation, backup policy enforcement, NSG/security list auditing, API key rotation status, encryption verification, and compliance monitoring via Cloud Guard. Use it when preparing an OCI environment for mission-critical workloads or conducting a formal security audit.

A comprehensive guide detailing how to establish robust monitoring for Qdrant. Covers setting up Prometheus metrics scraping, implementing Liveness and Readiness probes for Kubernetes, configuring alerts, and centralizing logs. It provides specific instructions for both self-hosted and Hybrid Cloud environments, ensuring full operational visibility and compliance.

This guide provides comprehensive guidance on scaling Qdrant, a vector database. It helps users diagnose performance bottlenecks and determine the optimal horizontal or vertical scaling strategy. Strategies are categorized based on specific needs: increasing data volume, improving query throughput (QPS), minimizing query latency, or managing high query result volumes.

This comprehensive guide provides advanced strategies for optimizing and scaling Qdrant vector database throughput (QPS). It covers performance tuning techniques, such as optimizing segment size, enabling quantization, and using batch search. Furthermore, it details horizontal scaling methods using read replicas and addressing disk I/O bottlenecks, ensuring high performance for large-scale, high-concurrency retrieval applications.

This component is an essential extension for KubeSphere Observability Platform, designed for comprehensive collection, processing, and storage of Kubernetes and KubeSphere audit events. It supports various sinks, including OpenSearch and Doris, and provides an API for querying historical audit data, ensuring robust auditing capabilities for platform operations.